Alternative IT Sourcing Strategies: Six Views

EDUCAUSE Review recently asked six CIOs to talk about alternative IT sourcing strategies and about whether they are, or aren’t, “doing it themselves”—providing technology services—at their institutions.

Cloud-sourcing. Outsourcing. Consortial sourcing. Institutional sourcing. Collaborative sourcing. Clearly, technologies and IT services are being delivered to colleges and universities in a myriad of ways. Whereas in the past the role of the IT organization was to provide IT services to the campus community—known (now) as insourcing—over time that role has subtly but concretely changed. IT leaders today must not only provide but also decide: which tools and services should they continue to supply, which are better delivered by others, and perhaps most critically, which methods from among the bewildering array of alternative sourcing strategies will best serve their faculty, staff, and students.

In 2009, the EDUCAUSE Center for Analysis and Research (ECAR) published Alternative IT Sourcing Strategies: From the Campus to the Cloud, by Philip Goldstein. The author defined “alternative sourcing” as “the range of options institutions have for providing technology services or operating technology functions aside from doing it themselves. This includes traditional outsourcing of all or part of the IT organization, accessing cloud services and externally managed applications, development environments, or hardware via the Internet, and use of contractors and consultants as a part of the IT organization.”

EDUCAUSE Review recently asked six CIOs to talk about alternative IT sourcing strategies and about whether they are, or aren’t, “doing it themselves” at their institutions.

The Cloud as an IT Sourcing Strategy

Ed Mahon
Vice President & CIO
Kent State University

IT leaders get it. It’s old news: reduced budgets, higher expectations, increased complexity, and shorter technology obsolescence periods. Further, we know the IT value proposition does not rest with baseline IT services (though no higher-level IT value can be obtained without these services).

With institutional budgets in crisis mode and increased demands on our IT investments, the need to thoroughly assess how we deliver both baseline IT support and IT development efforts has never been more critical. If you are having trouble keeping up with all the new service demands, a new service model, such as the cloud, may be a solution. To evaluate the cloud, we first need to ask: can the cloud be leveraged to develop new services more quickly and without spending more money than necessary? Sure, cloud service providers tout their features as forming a more scalable and elastic environment, all with a consumption-based utilization model, but is it true?

I think so.

Baseline Infrastructure Operations: Current State

Most IT departments have long since learned how to maintain the information infrastructure well. Reliable and relevant baseline IT services have become commonplace. Keeping the bits flowing and protected, maintaining a messaging environment, managing a multifaceted contact center, providing electronic storage solutions, and running data center services are routine operations. Most baseline services operate with three 9’s reliability (99.9% uptime). So why tinker with success by moving to other support models, such as the cloud’s Infrastructure as a Service (IaaS)?

To save money? If you are like me, you have not used the words “savings” and “IT” in the same sentence for years! We all know the difficulty inherent in measuring IT savings or cost reductions. The benefits often show up somewhere else in the academy, in the form of elevating a clerk to an analyst, reducing paper handling, improving customer satisfaction, or enhancing access to information. All are equally hard to measure, and any savings will likely not be in the IT budget.

Baseline Infrastructure Operations: Future State

Why risk a disruptive change in the support model if everything is working reliably? After all, the cloud is just another outsourcing solution, and we continuously evaluate outsourcing solutions. We select an outsourcing solution not to save money but to obtain a quality of service not otherwise obtainable on our own. Can the cloud actually provide higher-quality solutions by better leveraging advanced virtualization and storage techniques? Can the cloud really help with the unprecedented data growth—or at least control the costs? Some might suggest that the cloud is indeed about cost savings, but with a few exceptions, I don’t think savings is the key attribute. The most important benefits center around solving an age-old problem: the ratio of staff support to staff development. That is, cloud services can minimize operational costs, thereby increasing staff availability for IT development efforts.

I think of the cloud as a service-delivery model rather than a specific type of technology. The cloud offers the potential to deploy services faster by off-loading the tasks of buying, receiving, paying for, and installing hardware and software, patch management, change management, monitoring, and troubleshooting. The cloud also offers consumption-based pricing and capacity on demand. But again, the most valuable benefit is the opportunity to reduce distractions resulting from the maintenance operation and concurrently repurpose operational staff efforts toward developmental services.

Repurposing baseline services to the cloud sets the stage to better utilize full-time employees to learn institutional business needs and to build long-term relationships with the campus community. With more time for assessment, staff can develop a clearer understanding of the needs of the business or academic unit they serve. These service assessments can aid in the recruiting and retaining of students, can help simplify administrative processes, can improve the learning experience, and can support the research agenda.

A Difficult Move

Moving to the cloud is not a light-hearted, short-term endeavor. During the shift, running cloud services and premise-based systems concurrently for an extended period of time is difficult. The effort also requires one-time investment funds. The transition will be a multi-year effort that involves living in both worlds (accruing both on-premise and cloud-based costs). Finally, before moving to the cloud, IT leaders need to compare costs, develop new skills, and determine security requirements.

Comparing costs can be tricky. Learning the true fiscal impact of a consumption-based pricing model and confirming if capacity on demand will in fact meet peak usage needs should be at the root of cloud evaluation efforts. Leveling off or normalizing capital expenditures over time sounds attractive. Moving to a completely operational expenditure environment (no institution-owned equipment) may help develop a multiyear budget model, but doing so likely won’t reduce the expense of operations. Redesigning the existing activity based costing model in order to compare the actual costs of the current support model with that of the cloud prices will be challenging.

To ensure that service level agreements (SLAs) properly serve the new cloud-provider arrangement, IT leaders will need to develop new staff skills such as contract and vendor relationship management (truth is, we should already have these skills within our staff). Creating and managing SLAs within the contract to ensure key components such as monitoring, interoperability, data recovery and backup, real-time metrics, and the penalties that result from noncompliance will be required. The metrics tracked by cloud providers differ from those tracked by premise-based systems, requiring full-time staff to create and monitor these SLA measurements.

Lastly, IT leaders must determine which security requirements should be requested of cloud providers and how to ensure they are followed. Leaders should outline the security audit requirements and expectations of the cloud providers. Enhanced security may be more obtainable in the cloud, but we need techniques to verify that security.

The Cloud at the Application Level

With Software as a Service (SaaS), the vendor hosts the software application (in the cloud) and the customer provides the data to make it useful. This enables the application to be available from a browser anywhere.

Currently, complete institutional data systems such as enterprise resource planning (ERP) systems do not exist in the cloud for higher education (i.e., all tier-one modules integrated into a unified architecture in the cloud). Only a few traditional ERP modules are available in the cloud (employee benefits, payroll, procurement, finance, etc.). If you choose these SaaS offerings, plan for additional complexity and expense in order to integrate them with your core premise-based student information system. Building the interfaces needed to interconnect all applications will not be a new experience, but these interfaces differ in that they interconnect between multiple physical locations.

With limited sourcing options available for our institutional data systems, we will need to work with our ERP software providers to help define the maintenance efforts of these complex systems in order to implement a new ERP support model in the cloud. Additionally, potential shared services arrangements among institutions will also require this effort. Standardizing the ERP maintenance effort will be necessary no matter which option we select.

The Kent State Model

The Kent State University sourcing model involves an ongoing, multi-tiered assessment. First, we are ensuring that we maintain good relationships with our key vendors such as SunGard, Dell, Blackboard, Cisco, Microsoft, and Google and that we understand their future directions. It appears many of them are developing partnerships to provide enhanced services. My sense is that these partnerships will be needed in order to meet the needs of higher education. For example, Google and Blackboard could develop a more seamless collaboration space visible between their products, or Google and Cisco could ensure that unified communications and calendar presence work properly.

Second, we are updating our activity-based costing model that identifies current cost elements, per the business service they provide. The cost model doesn’t need to be exact in order to enable a cost comparison between all future support models, such as an operational expense-based model (OpEx) in the cloud.

Third, we are developing criteria to consider solutions that concurrently solve more than one problem, such as the following:

Outsourcing functions, such as moving our help desk to Blackboard, which would extend hours of operation without adding staff, deploy new services such as chat and scheduled call-back appointments via the web, and enable badged employees to create more useful knowledge database articles

Developing a daily back-up system that would also serve as a disaster-recovery method

Moving e-mail to the cloud (Gmail) to both save money and give students what they prefer

And finally, we are utilizing tier-one vendors’ partnership programs, such as SunGard’s tiered business system. Picking vendors that have already invested R&D dollars to integrate multiple software systems helps ensure that we don’t have to build duplicative API interfaces.

Conclusion

The difficulty in the cloud discussion lies in the transition, not in the decision to move to the cloud. Institutions will need to develop a sourcing strategy to manage their entry into the cloud. Though transition details will be complex, those of us in higher education have lived through such transitions before: mainframes and servers co-exist; UNIX and Windows operating systems co-exist. Cloud-based and premise-based computing support models will co-exist as well.